4. POINTS OF CONNECTION BETWEEN OGI AND PARAMETRIX OR PSU

The project described in Section 3 above was carefully designed to mesh with previous and on-going work performed by Parametrix (PMX) and Portland State University (PSU) during the RI/FS, risk assessment, and sediment transport phases of the slough restoration program. The table below outlines specific points of connection between keys OGI work products (as identified by task number) and activities of PMX or PSU.

TASK WITH CONNECTION
1.A PMX OGI and PMX sampling are complementary. PMX obtains a large number of spatially distributed samples and cores, but the large number resquires streamlining of sample handling. OGI will not capture spatial variation but can obtain more detailed chemical information about selected processes at fewer sites. OGI details should be generalizable to the broad sample data of PMX. The cumulative data thus will be stronger than the separate parts.
1.B/1.C PMX PMX data provide direct measures of apparent sediment/water partitioning for many locations. OGI data yield more general partition parameters for a few sites, but model results should be useful for interpreting the full range of PMX results and for generalizing risk assessments.
1.B/1.C PSU PSU sediment/contaminant transport model requires generalized partitioning parameters. The combined PMX and OGI data should provide robust estimates of these parameters.
1.E PMX The PMX SLRA made necessarily conservative assumptions about Cr being entirely in the most toxic form. OGI results will test this and allow revision of risk factors and action priorities.
2.A/2.B PMX OGI uptake/release data will allow PMX to verify equilibrium assumption in risk model.
2.A/2.B PSU OGI uptake/release data can be incorporated into PSU sediment transport model to enhance its accuracy and allow it to better predict movements and changes in contaminant concentrations in the future or under alternative remediation scenarios.
3.A/3.B PMX PMX bulk partitioning measurement are standard and essential for comparison but may not agree well with calculated values due to colloid-borne contaminants in pore water. And, colloid-borne contaminants are generally unavailable to biota so pore-water data may overestimate risk. OGI data will help PMX verify the meaning of their direct measurments and allow PMX to properly adjust pore-water data to compensate for a possible colloids effect.
3.A/3.B PSU PSU sediment transport model can be made more useful for assessing the consequences of remediation strategies if the mobilization of colloid-borne contaminants is taken into account by the use of the OGI data.
4.A PMX The PMX risk assessment models can be further generalized and refined if a more complete model of PCB distribution among slough components is available. The OGI fugacity modeling will reinforce previous PMX work on partitioning, particularly with respect to fish tissues and the possible (small) losses of PCB to the air.

TASK	WITH	CONNECTION
1.A	PMX	OGI and PMX sampling are complementary. PMX obtains a large number of spatially distributed samples and cores, but the large number resquires streamlining of sample handling. OGI will not capture spatial variation but can obtain more detailed chemical information about selected processes at fewer sites. OGI details should be generalizable to the broad sample data of PMX. The cumulative data thus will be stronger than the separate parts.
1.B/1.C	PMX	PMX data provide direct measures of apparent sediment/water partitioning for many locations. OGI data yield more general partition parameters for a few sites, but model results should be useful for interpreting the full range of PMX results and for generalizing risk assessments.
1.B/1.C	PSU	PSU sediment/contaminant transport model requires generalized partitioning parameters. The combined PMX and OGI data should provide robust estimates of these parameters.
1.E	PMX	The PMX SLRA made necessarily conservative assumptions about Cr being entirely in the most toxic form. OGI results will test this and allow revision of risk factors and action priorities.
2.A/2.B	PMX	OGI uptake/release data will allow PMX to verify equilibrium assumption in risk model.
2.A/2.B	PSU	OGI uptake/release data can be incorporated into PSU sediment transport model to enhance its accuracy and allow it to better predict movements and changes in contaminant concentrations in the future or under alternative remediation scenarios.
3.A/3.B	PMX	PMX bulk partitioning measurement are standard and essential for comparison but may not agree well with calculated values due to colloid-borne contaminants in pore water. And, colloid-borne contaminants are generally unavailable to biota so pore-water data may overestimate risk. OGI data will help PMX verify the meaning of their direct measurments and allow PMX to properly adjust pore-water data to compensate for a possible colloids effect.
3.A/3.B	PSU	PSU sediment transport model can be made more useful for assessing the consequences of remediation strategies if the mobilization of colloid-borne contaminants is taken into account by the use of the OGI data.
4.A	PMX	The PMX risk assessment models can be further generalized and refined if a more complete model of PCB distribution among slough components is available. The OGI fugacity modeling will reinforce previous PMX work on partitioning, particularly with respect to fish tissues and the possible (small) losses of PCB to the air.

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